{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:23:16.404525Z",
     "start_time": "2021-01-15T11:23:16.399156Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# FaceDetection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "- with high-level API (WebcamFaceDetector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:23:32.275770Z",
     "start_time": "2021-01-15T11:23:32.215641Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading ...\n",
      "from FaceDetector: weights loaded\n"
     ]
    }
   ],
   "source": [
    "from facelib import WebcamFaceDetector\n",
    "\n",
    "detector = WebcamFaceDetector()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:23:56.113604Z",
     "start_time": "2021-01-15T11:23:50.961215Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type q for exit\n"
     ]
    }
   ],
   "source": [
    "# please wait: it shows a window  \n",
    "detector.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T05:51:54.270802Z",
     "start_time": "2021-01-15T05:51:53.399871Z"
    },
    "hidden": true
   },
   "source": [
    "- with low-level API(FaceDetector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:23:09.667786Z",
     "start_time": "2021-01-15T11:23:04.242694Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "from FaceDetector: download defualt weight started\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 1.79M/1.79M [00:01<00:00, 968kiB/s] "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the default model weight donwloaded\n",
      "from FaceDetector: weights loaded\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from facelib import FaceDetector\n",
    "\n",
    "img = plt.imread('facelib/imgs/face_rec.jpg')\n",
    "detector = FaceDetector()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:23:20.125114Z",
     "start_time": "2021-01-15T11:23:19.795793Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "faces, boxes, scores, landmarks = detector.detect_align(img)\n",
    "plt.imshow(faces.cpu()[0]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# AgeGenderEstimator"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "- with high-level API (WebcamAgeGenderEstimator)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:24:26.347241Z",
     "start_time": "2021-01-15T11:24:18.753317Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading ...\n",
      "from FaceDetector: weights loaded\n",
      "from AgeGenderEstimator: download defualt weight started\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "5.17MiB [00:04, 1.06MiB/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the default model weight donwloaded\n",
      "from AgeGenderEstimator: weights loaded\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "from facelib import WebcamAgeGenderEstimator\n",
    "\n",
    "estimator = WebcamAgeGenderEstimator()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T06:59:54.325801Z",
     "start_time": "2021-01-15T06:59:50.237486Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type q for exit\n"
     ]
    }
   ],
   "source": [
    "# please wait: it shows a window  \n",
    "estimator.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "- with low-level API(FaceDetector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:24:32.683651Z",
     "start_time": "2021-01-15T11:24:32.590592Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "from FaceDetector: weights loaded\n",
      "from AgeGenderEstimator: weights loaded\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from facelib import AgeGenderEstimator, FaceDetector\n",
    "\n",
    "img = plt.imread('facelib/imgs/face_rec.jpg')\n",
    "face_detector = FaceDetector()\n",
    "age_gender_detector = AgeGenderEstimator()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T07:11:25.840525Z",
     "start_time": "2021-01-15T07:11:25.730643Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Male', 'Male'] [12, 11]\n"
     ]
    }
   ],
   "source": [
    "faces, boxes, scores, landmarks = face_detector.detect_align(img)\n",
    "genders, ages = age_gender_detector.detect(faces)\n",
    "print(genders, ages)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# FacialExpression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "- with high-level API (WebcamAgeGenderEstimator)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:26:17.089458Z",
     "start_time": "2021-01-15T11:26:15.682708Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading ...\n",
      "from FaceDetector: weights loaded\n",
      "from EmotionDetector: weights loaded\n"
     ]
    }
   ],
   "source": [
    "from facelib import WebcamEmotionDetector\n",
    "\n",
    "detector = WebcamEmotionDetector()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T07:10:29.499707Z",
     "start_time": "2021-01-15T07:10:23.008531Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type q for exit\n"
     ]
    }
   ],
   "source": [
    "# please wait: it shows a window\n",
    "detector.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "hidden": true
   },
   "source": [
    "- with low-level API(FaceDetector)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T07:11:48.843261Z",
     "start_time": "2021-01-15T07:11:48.417242Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "from FaceDetector: weights loaded\n",
      "from EmotionDetector: weights loaded\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from facelib import FaceDetector, EmotionDetector\n",
    "\n",
    "img = plt.imread('facelib/imgs/face_rec.jpg')\n",
    "face_detector = FaceDetector(face_size=(224, 224))\n",
    "emotion_detector = EmotionDetector()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T07:11:55.643712Z",
     "start_time": "2021-01-15T07:11:55.390106Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['happy' 'happy']\n"
     ]
    }
   ],
   "source": [
    "faces, boxes, scores, landmarks = face_detector.detect_align(img)\n",
    "list_of_emotions, probab = emotion_detector.detect_emotion(faces)\n",
    "print(list_of_emotions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "# Add New Person"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:26:51.907287Z",
     "start_time": "2021-01-15T11:26:44.971251Z"
    },
    "hidden": true,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading ...\n",
      "for exit: use q keyword\n",
      "from FaceDetector: weights loaded\n",
      "type q for exit\n",
      "images saved in this path:  facelib/InsightFace/models/data/facebank/sajjad\n"
     ]
    }
   ],
   "source": [
    "from facelib import add_from_webcam\n",
    "\n",
    "add_from_webcam(person_name='sajjad')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T08:33:58.950472Z",
     "start_time": "2021-01-15T08:33:58.088275Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "only a face in each image and all image from the same person\n",
      "loading ...\n",
      "from FaceDetector: weights loaded\n",
      "images saved in this path:  facelib/InsightFace/models/data/facebank/sajjad\n"
     ]
    }
   ],
   "source": [
    "from facelib import add_from_folder\n",
    "\n",
    "add_from_folder(person_name='sajjad', folder_path='./test/')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# FaceRecognition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- with high-level API (WebcamVerify)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:27:05.898581Z",
     "start_time": "2021-01-15T11:26:58.401863Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading ...\n",
      "from FaceDetector: weights loaded\n",
      "from FaceRecognizer: download defualt weight started\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "4.94MiB [00:04, 1.05MiB/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the default model weight donwloaded\n",
      "from FaceRecognizer: MobileFaceNet Loaded\n",
      "from FaceRecognizer: facebank updated\n"
     ]
    }
   ],
   "source": [
    "from facelib import WebcamVerify\n",
    "\n",
    "verifier = WebcamVerify()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:27:35.987264Z",
     "start_time": "2021-01-15T11:27:31.048755Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "type q for exit\n"
     ]
    }
   ],
   "source": [
    "# please wait: it shows a window\n",
    "verifier.run()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- with low-level API(FaceRecognizer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:28:21.901380Z",
     "start_time": "2021-01-15T11:28:21.711113Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "from FaceDetector: weights loaded\n",
      "from FaceRecognizer: MobileFaceNet Loaded\n",
      "from FaceRecognizer: facebank updated\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from facelib import FaceRecognizer, FaceDetector\n",
    "from facelib import update_facebank, load_facebank, special_draw, get_config\n",
    "\n",
    "conf = get_config()\n",
    "detector = FaceDetector()\n",
    "face_rec = FaceRecognizer(conf)\n",
    "face_rec.model.eval()\n",
    "\n",
    "update = True\n",
    "if update:\n",
    "    targets, names = update_facebank(conf, face_rec.model, detector)\n",
    "else:\n",
    "    targets, names = load_facebank(conf)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2021-01-15T11:28:22.986721Z",
     "start_time": "2021-01-15T11:28:22.726611Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['sajjad', 'Unknown'], dtype='<U7')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "img = plt.imread('facelib/imgs/face_rec.jpg')\n",
    "\n",
    "faces, boxes, scores, landmarks = detector.detect_align(img)\n",
    "results, score = face_rec.infer(conf, faces, targets)\n",
    "names[results.cpu()]"
   ]
  }
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